Confessions of a researchaholic

See here for the related post about how to do a rebuttal.

Again, this is mostly for SIGGRAPH, but likely applicable for other publication venues.

My answer is absolutely yes, for a very simple reason: the amount of time and efforts you spend on rebuttal will be a small percentage of what you have spent in submitting the paper (4 days versus months if not years). Thus, you have everything to gain, and little to lose.

More reasons:

. Review is a highly stochastic and unpredictable process, and nobody knows what is going to happen. I have seen papers with strong rating (e.g. > 4) rejected, and weak rating (e.g. < 2.8) accepted. (And yes, both are mine. And I was told the latter is a SIGGRAPH record.) . Not submitting a rebuttal is usually perceived by reviewers as a (negative) sign that authors agree with their (negative) comments. . Rebuttal is a good practice for both research method and emotion control, especially for students, junior researchers, and myself. . Show you get balls. As a reviewer I admire authors who can manage to come up with strong rebuttal even for a paper with low ratings.

As someone spending the first decade of career in the industry and the second in the academia, I am naturally very positive towards students taking internships. I can see several main benefits:

. Learning; especially for practical stuff that is very hard or impossible to obtain in school. One of the key lessons I got from NVIDIA is that “ideas that work in the academia usually do not work in practice”.

. Networking; you can know more people, many of who may turn out to be good mentors, friends, or referrals/references for your future career development.

. Experience; I particularly encourage internships in another country, culture, or continent. People with broader life experiences tend to be smarter, happier, more tolerant, and more creative. Or simply put, better.

However, not every internship is beneficial. I usually only recommend opportunities that (1) are with top companies/groups/individuals in our disciplines, such as MSR, NVIDIA, Adobe, Autodesk, and Disney for graphics or HCI, (2) provide projects that fit your research direction, and (3) allow my participation and (better) can be continued after the end of the internship (these will benefit everyone involved). So, I will not recommend internships with non-top hosts, coding/implementation projects involving little research, or secret topics that cannot lead to publications.

The main point of internship is for your learning, not for making money, which is the purpose of work, which you will have plenty opportunities to practice after you graduate. The distinction between work and internship is very important, and I will not allow part time jobs during your study.

About qualification: because I only work with top people, I can recommend only students whom I consider qualified; otherwise the student will either not get the internship, or (worse) not perform up to the expectation, which benefits nobody. So, just like my general principle of being the best, make sure you perform well with me, and having some SIGGRAPH/CHI papers definitely cannot hurt.
🙂

I am explaining this in the context of research/academic job hunting, but similar principles can be applied to other situations.

The effectiveness E of a particular individual as your reference can be expressed by the following equation:
E = wcQ
, where w is the weight of the individual, c the strength of the connection, and Q the quality of the recommendation.

In particular:

. w is the weight of that individual in the particular field you are applying your job for. A nobody has a weight with absolute value close to 0, while a bigwig has weight with absolutely value close to 1. Note the mention of absolute value; the weight can be positive as well as negative. (Think about having Charles Darwin as reference for a scientific versus theological post.)

. c is the strength of connection between you and that individual, a real number between 0 (e.g. you do not really know each other) and 1 (e.g. the two of you fought in the same foxhole during WWII).

. Q is the quality of recommendation, a real number between -1 (e.g. you did not realize you actually pissed off that guy) and 1 (e.g. you wrote a 1000+ citation paper with your PhD adviser).

Your job is to identify individuals who can give you sufficiently large E values. Thus, do not ask people who are not very successful (near 0 w) or (worse) are archenemies with the institution you are applying for (negative w), who barely know you (weak c), or who are too busy (near 0 Q) or too pissed (negative Q) to write good recommendation.

You want a reasonable number of large positive E values.
The definition of *reasonable number* is application dependent (pun intended), but I would say 5 is about right for a research/academic job, 3 will be a bit too weak, and you probably do not need more than 7 unless you are applying for a senior position.
Also, make sure your E values are all sufficiently large and positive; having a bunch of weak E will not help, and can give the impression that you have difficulty finding good references.

Last but not least, ask and obtain consensus from people before listing them as your references. It can be very impolite, and downright dangerous, if you do not do so.

If you feel these are all common senses, you will be surprised by how many people commit the very basic mistakes.